{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lesson 3: Basic Python for Data Analytics (Stocks Prediction)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction of Pandas\n",
    "\n",
    "\n",
    "pandas is a DataFrame Framework, a library that stores data in a highly efficient spreadsheet format and functions.\n",
    "Efficient in:\n",
    "1. Data Structure (numpy)\n",
    "2. Computing time (since DataFrame is processed by C++, it runs in a well streamlined computing environment)\n",
    "3. Highly optimized and updated processes\n",
    "\n",
    "\n",
    "[For more details of numpy](https://en.wikipedia.org/wiki/NumPy)\n",
    "\n",
    "[For more details of pandas cookbook and 10 minutes basic](http://pandas.pydata.org/pandas-docs/stable/10min.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objective\n",
    "\n",
    "* To use pandas to load the latest updated data from Yahoo Finance\n",
    "* To explore and understand the dataset \n",
    "    * Viewing the data\n",
    "    * Correlation Analysis\n",
    "    * Graphing using matplotlib\n",
    "* To predict the return of the stocks in the next period - Prediction analysis\n",
    "    * Simple Linear Analysis\n",
    "    * Quadratic Linear Analysis (QDA)\n",
    "    * K Nearest Neighbor (KNN)\n",
    "* Comparing models and discuss improvements\n",
    "* Challenges:\n",
    "    * Assuming economic qualitative factors such as news (news sourcing and sentimental analysis)\n",
    "    * Assuming economic quantitative factors such as HPI of a certain country, economic inequality among origin of company\n",
    "    * Cleaning out the data\n",
    "    * Importing data files\n",
    "* Next lesson:\n",
    "    * Lesson 4 Basic Python for Data Analytics (Predicting Employee Retention)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading YahooFinance Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this demonstration, we will use pandas web data reader. This is an extension of pandas library to communicate with most updated financial data. \n",
    "\n",
    "This will include sources as:\n",
    "* Yahoo! Finance\n",
    "* Google Finance\n",
    "* Enigma\n",
    "* FRED\n",
    "* Fama/French\n",
    "* World Bank\n",
    "* OECD\n",
    "* Eurostat\n",
    "* EDGAR Index\n",
    "* TSP Fund Data\n",
    "* Oanda currency historical rate\n",
    "* Nasdaq Trader Symbol Definitions\n",
    "\n",
    "[For more details of pandas webreader](https://pandas-datareader.readthedocs.io/en/latest/)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>115.919998</td>\n",
       "      <td>116.860001</td>\n",
       "      <td>115.809998</td>\n",
       "      <td>116.610001</td>\n",
       "      <td>22103700</td>\n",
       "      <td>116.610001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>116.779999</td>\n",
       "      <td>118.160004</td>\n",
       "      <td>116.470001</td>\n",
       "      <td>117.910004</td>\n",
       "      <td>31577900</td>\n",
       "      <td>117.910004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>117.949997</td>\n",
       "      <td>119.430000</td>\n",
       "      <td>117.940002</td>\n",
       "      <td>118.989998</td>\n",
       "      <td>33387600</td>\n",
       "      <td>118.989998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>118.769997</td>\n",
       "      <td>119.379997</td>\n",
       "      <td>118.300003</td>\n",
       "      <td>119.110001</td>\n",
       "      <td>24420800</td>\n",
       "      <td>119.110001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>118.739998</td>\n",
       "      <td>119.930000</td>\n",
       "      <td>118.599998</td>\n",
       "      <td>119.750000</td>\n",
       "      <td>27418600</td>\n",
       "      <td>119.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close    Volume  \\\n",
       "Date                                                                   \n",
       "2017-01-05  115.919998  116.860001  115.809998  116.610001  22103700   \n",
       "2017-01-06  116.779999  118.160004  116.470001  117.910004  31577900   \n",
       "2017-01-09  117.949997  119.430000  117.940002  118.989998  33387600   \n",
       "2017-01-10  118.769997  119.379997  118.300003  119.110001  24420800   \n",
       "2017-01-11  118.739998  119.930000  118.599998  119.750000  27418600   \n",
       "\n",
       "             Adj Close  \n",
       "Date                    \n",
       "2017-01-05  116.610001  \n",
       "2017-01-06  117.910004  \n",
       "2017-01-09  118.989998  \n",
       "2017-01-10  119.110001  \n",
       "2017-01-11  119.750000  "
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import datetime\n",
    "import pandas_datareader.data as web\n",
    "from pandas import Series, DataFrame\n",
    "\n",
    "\n",
    "start = datetime.datetime(2010, 1, 1)\n",
    "end = datetime.datetime.now()\n",
    "\n",
    "df = web.DataReader(\"AAPL\", 'yahoo', start, end)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the dimension of dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1769, 6)"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring the data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we will need to explore the data.\n",
    "This means understanding the stocks data trend thoroughly by finding key measures\n",
    "* rolling mean (moving average) -- to determine trend\n",
    "* return deviation -- to determine return deviation\n",
    "\n",
    "[For more details of rolling mean](http://www.investopedia.com/articles/active-trading/052014/how-use-moving-average-buy-stocks.asp) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2016-12-28    111.508340\n",
       "2016-12-29    111.597476\n",
       "2016-12-30    111.673134\n",
       "2017-01-03    111.760151\n",
       "2017-01-04    111.846564\n",
       "2017-01-05    111.936389\n",
       "2017-01-06    112.026282\n",
       "2017-01-09    112.127969\n",
       "2017-01-10    112.232448\n",
       "2017-01-11    112.344720\n",
       "Name: Adj Close, dtype: float64"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_px = df['Adj Close']\n",
    "mavg = close_px.rolling(window=100).mean()\n",
    "mavg.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x106dd320>"
      ]
     },
     "execution_count": 308,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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PysZqjnNGsHAsVm/6TvX5p8b9Z4v7PmtGFrS5U1U6Hb1yRmv/cTPavPMDz5ed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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106dd550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "\n",
    "# Adjusting the size of matplotlib\n",
    "import matplotlib as mpl\n",
    "mpl.rc('figure', figsize=(8, 7))\n",
    "mpl.__version__\n",
    "\n",
    "# Adjusting the style of matplotlib\n",
    "style.use('ggplot')\n",
    "\n",
    "close_px.plot(label='AAPL')\n",
    "mavg.plot(label='mavg')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Returns defined as: \n",
    "$$ $$\n",
    "$$r_t = \\frac{p_t - p_{t-1}}{p_{t-1}} = \\frac{p_t}{p_{t-1}} - 1$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2010-01-04         NaN\n",
       "2010-01-05    0.001729\n",
       "2010-01-06   -0.015906\n",
       "2010-01-07   -0.001849\n",
       "2010-01-08    0.006648\n",
       "Name: Adj Close, dtype: float64"
      ]
     },
     "execution_count": 309,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets = close_px / close_px.shift(1) - 1\n",
    "rets.head()\n",
    "\n",
    "# close_px.pct_change().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc0b9160>"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ozOxKJxmbR49NvQjnMmrm/ulHwr/49OCHxsweaV3c7mX0uX8HFgJGwqNY0YZE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\nxmcwh8swNFBy8KejkJHe0acF21tuH2oe/WEoyaJik8sGSHz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1rd2laAGtrffeQz6HTf0T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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106ddc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rets.plot(label='return')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Doing the competitor analysis/Correlation\n",
    "\n",
    "1. How does one company perform in relative with its competitor\n",
    "2. What are the correlations among these companies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>GE</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>116.610001</td>\n",
       "      <td>31.520000</td>\n",
       "      <td>794.020020</td>\n",
       "      <td>168.699997</td>\n",
       "      <td>62.299999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>117.910004</td>\n",
       "      <td>31.610001</td>\n",
       "      <td>806.150024</td>\n",
       "      <td>169.529999</td>\n",
       "      <td>62.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>118.989998</td>\n",
       "      <td>31.459999</td>\n",
       "      <td>806.650024</td>\n",
       "      <td>167.649994</td>\n",
       "      <td>62.639999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>119.110001</td>\n",
       "      <td>31.370001</td>\n",
       "      <td>804.789978</td>\n",
       "      <td>165.520004</td>\n",
       "      <td>62.619999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>119.750000</td>\n",
       "      <td>31.469999</td>\n",
       "      <td>807.909973</td>\n",
       "      <td>167.750000</td>\n",
       "      <td>63.189999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  AAPL         GE        GOOG         IBM       MSFT\n",
       "Date                                                                \n",
       "2017-01-05  116.610001  31.520000  794.020020  168.699997  62.299999\n",
       "2017-01-06  117.910004  31.610001  806.150024  169.529999  62.840000\n",
       "2017-01-09  118.989998  31.459999  806.650024  167.649994  62.639999\n",
       "2017-01-10  119.110001  31.370001  804.789978  165.520004  62.619999\n",
       "2017-01-11  119.750000  31.469999  807.909973  167.750000  63.189999"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfcomp = web.DataReader(['AAPL', 'GE', 'GOOG', 'IBM', 'MSFT'],'yahoo',\n",
    "                               start=start, \n",
    "                               end=end)['Adj Close']\n",
    "dfcomp.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the dimension of dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1769, 5)"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfcomp.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>GE</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.381502</td>\n",
       "      <td>0.411549</td>\n",
       "      <td>0.383906</td>\n",
       "      <td>0.393467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GE</th>\n",
       "      <td>0.381502</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.422241</td>\n",
       "      <td>0.535501</td>\n",
       "      <td>0.474070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>0.411549</td>\n",
       "      <td>0.422241</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.402790</td>\n",
       "      <td>0.472016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>0.383906</td>\n",
       "      <td>0.535501</td>\n",
       "      <td>0.402790</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.496905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>0.393467</td>\n",
       "      <td>0.474070</td>\n",
       "      <td>0.472016</td>\n",
       "      <td>0.496905</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          AAPL        GE      GOOG       IBM      MSFT\n",
       "AAPL  1.000000  0.381502  0.411549  0.383906  0.393467\n",
       "GE    0.381502  1.000000  0.422241  0.535501  0.474070\n",
       "GOOG  0.411549  0.422241  1.000000  0.402790  0.472016\n",
       "IBM   0.383906  0.535501  0.402790  1.000000  0.496905\n",
       "MSFT  0.393467  0.474070  0.472016  0.496905  1.000000"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retscomp = dfcomp.pct_change()\n",
    "\n",
    "corr = retscomp.corr()\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11ea5208>"
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YMmAA8dFHH+GBBx7Qv46Pj8dbb70FAKitrcWRI0cYQBDRuFNXJ8FqxXUFAsNxLFWShJg+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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c86358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(retscomp.AAPL, retscomp.GE)\n",
    "plt.xlabel('Returns AAPL')\n",
    "plt.ylabel('Returns GE')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can do scatter matrix with all the competitors data and find the kde of each m\n",
    "KDE will determine if your chart is more normally distributed leaning to the \n",
    "* left: Returns are more likely to be negative in the long run\n",
    "* centre: Returns are more likely to be 0 in the long run\n",
    "* right: Returns are more likely to be positive in the long run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Nrs/ZXK84/OBahUrLx3J8Xj5eRBJFTEXk+YEs5ZTC2e4UhiLQ9iNaXqwESGIc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\nwVQkckUXD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R67UyZ9UY0TMxZ/eybNiWlrxfjSgNZmLbIOtXktbbtky1UuL5aYyJToCGsY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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc3b68d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.scatter_matrix(retscomp, diagonal='kde', figsize=(10, 10));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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af8iQIV0RBgAgQFi1rewPXZKI169fL0mKi4vTK6+80u46w4YN07Bhwy6aP3Xq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12c374e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(corr, cmap='hot', interpolation='none')\n",
    "plt.colorbar()\n",
    "plt.xticks(range(len(corr)), corr.columns)\n",
    "plt.yticks(range(len(corr)), corr.columns);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stocks mean and Risk calculation\n",
    "Which stocks are risky and bearing returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kurtosis and skewness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CXq9Xu3bt0p49e5SXl6c77rhDvXuf2Z3iAKA1oVAvNTScK+ncU7b9+9976dFH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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15d9d9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(retscomp.mean(), retscomp.std())\n",
    "plt.xlabel('Expected returns')\n",
    "plt.ylabel('Risk')\n",
    "for label, x, y in zip(retscomp.columns, retscomp.mean(), retscomp.std()):\n",
    "    plt.annotate(\n",
    "        label, \n",
    "        xy = (x, y), xytext = (20, -20),\n",
    "        textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "        bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),\n",
    "        arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting the stocks price"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To predict the return of the stocks in the next period - Prediction analysis\n",
    "* Simple Linear Analysis\n",
    "* Quadratic Linear Analysis (QDA)\n",
    "* K Nearest Neighbor (KNN)\n",
    "\n",
    "But first, let us extract the necessary columns first from df:\n",
    "* Adj Close\n",
    "* Adj Volume\n",
    "* HL Percentage\n",
    "* PCT Change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>213.429998</td>\n",
       "      <td>214.499996</td>\n",
       "      <td>212.380001</td>\n",
       "      <td>214.009998</td>\n",
       "      <td>123432400</td>\n",
       "      <td>27.847252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>214.599998</td>\n",
       "      <td>215.589994</td>\n",
       "      <td>213.249994</td>\n",
       "      <td>214.379993</td>\n",
       "      <td>150476200</td>\n",
       "      <td>27.895396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>214.379993</td>\n",
       "      <td>215.230000</td>\n",
       "      <td>210.750004</td>\n",
       "      <td>210.969995</td>\n",
       "      <td>138040000</td>\n",
       "      <td>27.451683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>211.750000</td>\n",
       "      <td>212.000006</td>\n",
       "      <td>209.050005</td>\n",
       "      <td>210.580000</td>\n",
       "      <td>119282800</td>\n",
       "      <td>27.400936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>210.299994</td>\n",
       "      <td>212.000006</td>\n",
       "      <td>209.060005</td>\n",
       "      <td>211.980005</td>\n",
       "      <td>111902700</td>\n",
       "      <td>27.583106</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close     Volume  \\\n",
       "Date                                                                    \n",
       "2010-01-04  213.429998  214.499996  212.380001  214.009998  123432400   \n",
       "2010-01-05  214.599998  215.589994  213.249994  214.379993  150476200   \n",
       "2010-01-06  214.379993  215.230000  210.750004  210.969995  138040000   \n",
       "2010-01-07  211.750000  212.000006  209.050005  210.580000  119282800   \n",
       "2010-01-08  210.299994  212.000006  209.060005  211.980005  111902700   \n",
       "\n",
       "            Adj Close  \n",
       "Date                   \n",
       "2010-01-04  27.847252  \n",
       "2010-01-05  27.895396  \n",
       "2010-01-06  27.451683  \n",
       "2010-01-07  27.400936  \n",
       "2010-01-08  27.583106  "
      ]
     },
     "execution_count": 318,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>HL_PCT</th>\n",
       "      <th>PCT_change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>27.847252</td>\n",
       "      <td>123432400</td>\n",
       "      <td>0.990606</td>\n",
       "      <td>0.271752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>27.895396</td>\n",
       "      <td>150476200</td>\n",
       "      <td>1.091520</td>\n",
       "      <td>-0.102519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>27.451683</td>\n",
       "      <td>138040000</td>\n",
       "      <td>2.123523</td>\n",
       "      <td>-1.590633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>27.400936</td>\n",
       "      <td>119282800</td>\n",
       "      <td>1.400893</td>\n",
       "      <td>-0.552538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>27.583106</td>\n",
       "      <td>111902700</td>\n",
       "      <td>1.386924</td>\n",
       "      <td>0.798864</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Adj Close     Volume    HL_PCT  PCT_change\n",
       "Date                                                  \n",
       "2010-01-04  27.847252  123432400  0.990606    0.271752\n",
       "2010-01-05  27.895396  150476200  1.091520   -0.102519\n",
       "2010-01-06  27.451683  138040000  2.123523   -1.590633\n",
       "2010-01-07  27.400936  119282800  1.400893   -0.552538\n",
       "2010-01-08  27.583106  111902700  1.386924    0.798864"
      ]
     },
     "execution_count": 319,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfreg = df.loc[:,['Adj Close','Volume']]\n",
    "dfreg['HL_PCT'] = (df['High'] - df['Low']) / df['Close'] * 100.0\n",
    "dfreg['PCT_change'] = (df['Close'] - df['Open']) / df['Open'] * 100.0\n",
    "dfreg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1769, 4)\n",
      "('Dimension of X', (1751L, 4L))\n",
      "('Dimension of y', (1751L,))\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "import numpy as np\n",
    "from sklearn import preprocessing, cross_validation, svm\n",
    "\n",
    "\n",
    "# Drop missing value\n",
    "dfreg.fillna(value=-99999, inplace=True)\n",
    "\n",
    "print(dfreg.shape)\n",
    "# We want to separate 1 percent of the data to forecast\n",
    "forecast_out = int(math.ceil(0.01 * len(dfreg)))\n",
    "\n",
    "# Separating the label here, we want to predict the AdjClose\n",
    "forecast_col = 'Adj Close'\n",
    "dfreg['label'] = dfreg[forecast_col].shift(-forecast_out)\n",
    "X = np.array(dfreg.drop(['label'], 1))\n",
    "\n",
    "# Scale the X so that everyone can have the same distribution for linear regression\n",
    "X = preprocessing.scale(X)\n",
    "\n",
    "# Finally We want to find Data Series of late X and early X (train) for model generation and evaluation\n",
    "X_lately = X[-forecast_out:]\n",
    "X = X[:-forecast_out]\n",
    "\n",
    "# Separate label and identify it as y\n",
    "y = np.array(dfreg['label'])\n",
    "y = y[:-forecast_out]\n",
    "\n",
    "print('Dimension of X',X.shape)\n",
    "print('Dimension of y',y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separation of training and testing of model by cross validation train test split\n",
    "X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Generation\n",
    "\n",
    "* To predict the return of the stocks in the next period - Prediction analysis\n",
    "    * Simple Linear Analysis\n",
    "    * Quadratic Linear Analysis (QDA)\n",
    "    * K Nearest Neighbor (KNN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "          metric_params=None, n_jobs=1, n_neighbors=2, p=2,\n",
       "          weights='uniform')"
      ]
     },
     "execution_count": 322,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "# Linear regression\n",
    "clfreg = LinearRegression(n_jobs=-1)\n",
    "clfreg.fit(X_train, y_train)\n",
    "\n",
    "\n",
    "# Quadratic Regression 2\n",
    "clfpoly2 = make_pipeline(PolynomialFeatures(2), Ridge())\n",
    "clfpoly2.fit(X_train, y_train)\n",
    "\n",
    "# Quadratic Regression 3\n",
    "clfpoly3 = make_pipeline(PolynomialFeatures(3), Ridge())\n",
    "clfpoly3.fit(X_train, y_train)\n",
    "    \n",
    "# KNN Regression\n",
    "clfknn = KNeighborsRegressor(n_neighbors=2)\n",
    "clfknn.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('The linear regression confidence is ', 0.96399641826551985)\n",
      "('The quadratic regression 2 confidence is ', 0.96492624557970319)\n",
      "('The quadratic regression 3 confidence is ', 0.9652082834532858)\n",
      "('The knn regression confidence is ', 0.92844658034790639)\n"
     ]
    }
   ],
   "source": [
    "confidencereg = clfreg.score(X_test, y_test)\n",
    "confidencepoly2 = clfpoly2.score(X_test,y_test)\n",
    "confidencepoly3 = clfpoly3.score(X_test,y_test)\n",
    "confidenceknn = clfknn.score(X_test, y_test)\n",
    "\n",
    "print(\"The linear regression confidence is \",confidencereg)\n",
    "print(\"The quadratic regression 2 confidence is \",confidencepoly2)\n",
    "print(\"The quadratic regression 3 confidence is \",confidencepoly3)\n",
    "print(\"The knn regression confidence is \",confidenceknn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This means that the linear regression holds the most accuracy of it as being linear and justify the trend of stocks as being linear most of the times. \n",
    "\n",
    "However this does not mean we can just put stocks in it. There are still many issues to consider, especially with different companies that have different price trajectories over time. Google really is very linear: Up and to the right. Many companies aren't, so keep this in mind. \n",
    "\n",
    "We need to plot out the graph to make the most sense of it "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([ 115.44941187,  115.20206522,  116.78688393,  116.70244946,\n",
      "        116.58503739,  115.98769407,  116.54315699,  117.40012338,\n",
      "        117.21473053,  116.57244657,  116.048717  ,  116.26444966,\n",
      "        115.78374093,  116.50647805,  117.92064806,  118.75581186,\n",
      "        118.82688731,  119.51873699]), 0.96234891774075604, 18)\n"
     ]
    }
   ],
   "source": [
    "# Printing the forecast\n",
    "forecast_set = clf.predict(X_lately)\n",
    "dfreg['Forecast'] = np.nan\n",
    "print(forecast_set, confidence, forecast_out)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting the Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "last_date = dfreg.iloc[-1].name\n",
    "last_unix = last_date\n",
    "next_unix = last_unix + datetime.timedelta(days=1)\n",
    "\n",
    "for i in forecast_set:\n",
    "    next_date = next_unix\n",
    "    next_unix += datetime.timedelta(days=1)\n",
    "    dfreg.loc[next_date] = [np.nan for _ in range(len(dfreg.columns)-1)]+[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nycQ7NX0ojQN1/muxPnUTKAsaVrDIu9xQoCWPrwVa2lHbz1xRw2p0KGgeSDMg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\nMGiS6mZLvIPcyXfxuEkUyoN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V9PTM/DAfeeQRzj//fFwuF52dnfT09HDw4MGlWqpQSeSq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\nNabePkWsAoXU12wS76ai5rekyphV5O+99960yP/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vKg6EzHg3aCIwWMsKZzJBuwcF+dbW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+zsr3/9K5WVlVx66aWusjr/37JlCzabjb1797Jv3z6mTp2q+/FogOLiYjZt2kRwcDBff/01b731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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15c38cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfreg['Adj Close'].tail(500).plot()\n",
    "dfreg['Forecast'].tail(500).plot()\n",
    "plt.legend(loc=4)\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Challenges (To Be Continued):\n",
    "* Assuming economic qualitative factors such as news (news sourcing and sentimental analysis)\n",
    "* Assuming economic quantitative factors such as HPI of a certain country, economic inequality among origin of company\n",
    "* Cleaning out the data\n",
    "* Importing data files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Next lesson:\n",
    "## Lesson 4 Basic Python for Data Analytics (Predicting Employee Retention)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
